Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "190"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 190 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 29 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 27 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 190, Node N15:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459846 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 66.617416 28.995929 4.519809 35.497001 14.575075 54.975866 44.602103 391.683176 0.6151 0.0309 0.4683 3.757451 1.365257
2459844 digital_ok 100.00% 100.00% 100.00% 0.00% - - 10.219037 15.557088 3.649125 8.937379 0.954469 4.849678 0.013930 12.567522 0.0251 0.0233 0.0012 nan nan
2459842 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 37.647621 13.835867 -0.327075 10.101259 11.967187 -0.522693 31.958962 1.519575 0.5319 0.0328 0.3952 4.630519 1.275210
2459841 digital_ok 100.00% 100.00% 100.00% 0.00% - - 11.766325 14.516097 1.670336 6.166017 1.779497 6.898227 1.368433 10.241438 0.0251 0.0236 0.0010 nan nan
2459839 digital_ok 100.00% - - - - - 0.486199 1.951405 0.172743 0.938185 0.859767 2.102877 0.887054 9.507434 nan nan nan nan nan
2459838 digital_ok 100.00% 12.26% 100.00% 0.00% 100.00% 0.00% 66.690621 22.822740 3.711100 24.138612 19.127579 29.919984 9.587032 2.342363 0.5312 0.0458 0.3980 0.000000 0.000000
2459836 digital_ok - 100.00% 100.00% 0.00% - - nan nan nan nan nan nan nan nan 0.0415 0.0449 0.0090 nan nan
2459835 digital_ok 0.00% 100.00% 100.00% 0.00% - - 0.203921 2.352664 -0.799446 2.887510 -0.947157 -0.273532 -0.949515 1.395427 0.0385 0.0483 0.0091 nan nan
2459833 digital_ok 100.00% 100.00% 100.00% 0.00% - - 5.097383 4.722270 0.353091 3.893050 1.945874 2.910092 -0.179285 12.200689 0.0334 0.0534 0.0034 nan nan
2459832 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 84.540198 39.737760 3.150667 26.496157 8.663956 11.783088 21.056259 2.743346 0.6225 0.0431 0.4943 3.359670 1.441830
2459831 digital_ok 100.00% 100.00% 100.00% 0.00% - - 0.411353 2.069005 0.012190 1.011745 1.294503 2.439240 0.518471 7.428554 0.0300 0.0277 0.0021 nan nan
2459830 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 71.840450 38.813530 3.131867 37.606854 24.045396 36.130252 23.637330 6.548844 0.6755 0.0409 0.4500 3.314339 1.069224
2459829 digital_ok 100.00% 11.82% 100.00% 0.00% 100.00% 0.00% 99.097545 39.078679 3.766669 30.707748 18.167801 32.183343 10.562182 8.733263 0.5283 0.0421 0.3527 0.000000 0.000000
2459828 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 58.106853 32.265009 2.821107 32.799617 14.959246 33.339987 79.317400 13.415901 0.6512 0.0451 0.4478 0.000000 0.000000
2459827 digital_ok 100.00% 15.04% 100.00% 0.00% 100.00% 0.00% 75.854462 29.977024 5.235608 37.468333 15.326430 26.315620 109.386530 1.865611 0.5317 0.0427 0.3181 3.864798 1.380583
2459826 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 58.927464 29.204004 4.756377 41.312234 22.050304 45.246022 2.495538 8.734999 0.6491 0.0449 0.4245 0.000000 0.000000
2459825 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 57.356112 32.073902 2.860385 33.203276 23.758611 30.046612 53.663661 4.426345 0.6483 0.0415 0.3595 0.000000 0.000000
2459824 digital_ok 100.00% 16.03% 100.00% 0.00% 100.00% 0.00% 63.350169 22.752909 3.658320 26.990515 13.670164 23.334840 13.920609 9.366384 0.4889 0.0402 0.2518 0.000000 0.000000
2459823 digital_ok 100.00% 18.82% 100.00% 0.00% 100.00% 0.00% 29.313380 27.076991 2.332616 48.790199 21.763454 36.047252 65.020554 32.204252 0.5887 0.0389 0.3251 0.000000 0.000000
2459822 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 33.510730 29.472632 2.131387 44.896870 9.692739 29.611515 63.453638 1.325346 0.6991 0.0444 0.3917 0.000000 0.000000
2459821 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 34.559561 31.040336 1.951426 45.739592 9.330736 27.687229 32.528138 1.300725 0.6824 0.0426 0.4394 5.545904 1.719189
2459820 digital_ok 100.00% 8.06% 100.00% 0.00% 100.00% 0.00% 77.242125 29.532492 5.423476 37.361485 36.876631 69.397207 16.350442 5.854430 0.5731 0.0501 0.3777 0.000000 0.000000
2459817 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 42.581791 26.804295 2.892031 44.383923 18.261230 36.861417 26.248594 4.612267 0.6781 0.0470 0.4618 0.000000 0.000000
2459816 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 43.926725 23.350212 3.278840 45.250507 24.135977 45.365555 31.022669 9.114476 0.7217 0.0452 0.5604 2.595323 0.945403
2459815 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 41.071773 25.125147 3.929624 48.688937 19.088373 48.155475 12.763033 13.215234 0.6331 0.0415 0.4564 2.466737 0.969552
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 190: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Temporal Discontinuties 391.683176 66.617416 28.995929 4.519809 35.497001 14.575075 54.975866 44.602103 391.683176

Antenna 190: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Shape 15.557088 10.219037 15.557088 3.649125 8.937379 0.954469 4.849678 0.013930 12.567522

Antenna 190: 2459842

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Shape 37.647621 37.647621 13.835867 -0.327075 10.101259 11.967187 -0.522693 31.958962 1.519575

Antenna 190: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Shape 14.516097 11.766325 14.516097 1.670336 6.166017 1.779497 6.898227 1.368433 10.241438

Antenna 190: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Temporal Discontinuties 9.507434 1.951405 0.486199 0.938185 0.172743 2.102877 0.859767 9.507434 0.887054

Antenna 190: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Shape 66.690621 22.822740 66.690621 24.138612 3.711100 29.919984 19.127579 2.342363 9.587032

Antenna 190: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Power 2.887510 2.352664 0.203921 2.887510 -0.799446 -0.273532 -0.947157 1.395427 -0.949515

Antenna 190: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Temporal Discontinuties 12.200689 4.722270 5.097383 3.893050 0.353091 2.910092 1.945874 12.200689 -0.179285

Antenna 190: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Shape 84.540198 84.540198 39.737760 3.150667 26.496157 8.663956 11.783088 21.056259 2.743346

Antenna 190: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Temporal Discontinuties 7.428554 0.411353 2.069005 0.012190 1.011745 1.294503 2.439240 0.518471 7.428554

Antenna 190: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Shape 71.840450 71.840450 38.813530 3.131867 37.606854 24.045396 36.130252 23.637330 6.548844

Antenna 190: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Shape 99.097545 39.078679 99.097545 30.707748 3.766669 32.183343 18.167801 8.733263 10.562182

Antenna 190: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Temporal Discontinuties 79.317400 32.265009 58.106853 32.799617 2.821107 33.339987 14.959246 13.415901 79.317400

Antenna 190: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Temporal Discontinuties 109.386530 75.854462 29.977024 5.235608 37.468333 15.326430 26.315620 109.386530 1.865611

Antenna 190: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Shape 58.927464 29.204004 58.927464 41.312234 4.756377 45.246022 22.050304 8.734999 2.495538

Antenna 190: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Shape 57.356112 32.073902 57.356112 33.203276 2.860385 30.046612 23.758611 4.426345 53.663661

Antenna 190: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Shape 63.350169 63.350169 22.752909 3.658320 26.990515 13.670164 23.334840 13.920609 9.366384

Antenna 190: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Temporal Discontinuties 65.020554 27.076991 29.313380 48.790199 2.332616 36.047252 21.763454 32.204252 65.020554

Antenna 190: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Temporal Discontinuties 63.453638 33.510730 29.472632 2.131387 44.896870 9.692739 29.611515 63.453638 1.325346

Antenna 190: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Power 45.739592 31.040336 34.559561 45.739592 1.951426 27.687229 9.330736 1.300725 32.528138

Antenna 190: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok ee Shape 77.242125 77.242125 29.532492 5.423476 37.361485 36.876631 69.397207 16.350442 5.854430

Antenna 190: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Power 44.383923 42.581791 26.804295 2.892031 44.383923 18.261230 36.861417 26.248594 4.612267

Antenna 190: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Temporal Variability 45.365555 23.350212 43.926725 45.250507 3.278840 45.365555 24.135977 9.114476 31.022669

Antenna 190: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Power 48.688937 25.125147 41.071773 48.688937 3.929624 48.155475 19.088373 13.215234 12.763033

Antenna 190: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 190: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
190 N15 digital_ok nn Shape nan nan nan inf inf nan nan nan nan
In [ ]: